Struct google_api_proto::google::cloud::automl::v1::BatchPredictRequest
source · pub struct BatchPredictRequest {
pub name: String,
pub input_config: Option<BatchPredictInputConfig>,
pub output_config: Option<BatchPredictOutputConfig>,
pub params: BTreeMap<String, String>,
}
Expand description
Request message for [PredictionService.BatchPredict][google.cloud.automl.v1.PredictionService.BatchPredict].
Fields§
§name: String
Required. Name of the model requested to serve the batch prediction.
input_config: Option<BatchPredictInputConfig>
Required. The input configuration for batch prediction.
output_config: Option<BatchPredictOutputConfig>
Required. The Configuration specifying where output predictions should be written.
params: BTreeMap<String, String>
Additional domain-specific parameters for the predictions, any string must be up to 25000 characters long.
AutoML Natural Language Classification
score_threshold
: (float) A value from 0.0 to 1.0. When the model
makes predictions for a text snippet, it will only produce results
that have at least this confidence score. The default is 0.5.
AutoML Vision Classification
score_threshold
: (float) A value from 0.0 to 1.0. When the model
makes predictions for an image, it will only produce results that
have at least this confidence score. The default is 0.5.
AutoML Vision Object Detection
score_threshold
: (float) When Model detects objects on the image,
it will only produce bounding boxes which have at least this
confidence score. Value in 0 to 1 range, default is 0.5.
max_bounding_box_count
: (int64) The maximum number of bounding
boxes returned per image. The default is 100, the
number of bounding boxes returned might be limited by the server.
AutoML Video Intelligence Classification
score_threshold
: (float) A value from 0.0 to 1.0. When the model
makes predictions for a video, it will only produce results that
have at least this confidence score. The default is 0.5.
segment_classification
: (boolean) Set to true to request
segment-level classification. AutoML Video Intelligence returns
labels and their confidence scores for the entire segment of the
video that user specified in the request configuration.
The default is true.
shot_classification
: (boolean) Set to true to request shot-level
classification. AutoML Video Intelligence determines the boundaries
for each camera shot in the entire segment of the video that user
specified in the request configuration. AutoML Video Intelligence
then returns labels and their confidence scores for each detected
shot, along with the start and end time of the shot.
The default is false.
WARNING: Model evaluation is not done for this classification type, the quality of it depends on training data, but there are no metrics provided to describe that quality.
1s_interval_classification
: (boolean) Set to true to request
classification for a video at one-second intervals. AutoML Video
Intelligence returns labels and their confidence scores for each
second of the entire segment of the video that user specified in the
request configuration. The default is false.
WARNING: Model evaluation is not done for this classification type, the quality of it depends on training data, but there are no metrics provided to describe that quality.
AutoML Video Intelligence Object Tracking
score_threshold
: (float) When Model detects objects on video frames,
it will only produce bounding boxes which have at least this
confidence score. Value in 0 to 1 range, default is 0.5.
max_bounding_box_count
: (int64) The maximum number of bounding
boxes returned per image. The default is 100, the
number of bounding boxes returned might be limited by the server.
min_bounding_box_size
: (float) Only bounding boxes with shortest edge
at least that long as a relative value of video frame size are
returned. Value in 0 to 1 range. Default is 0.
Trait Implementations§
source§impl Clone for BatchPredictRequest
impl Clone for BatchPredictRequest
source§fn clone(&self) -> BatchPredictRequest
fn clone(&self) -> BatchPredictRequest
1.0.0 · source§fn clone_from(&mut self, source: &Self)
fn clone_from(&mut self, source: &Self)
source
. Read moresource§impl Debug for BatchPredictRequest
impl Debug for BatchPredictRequest
source§impl Default for BatchPredictRequest
impl Default for BatchPredictRequest
source§impl Message for BatchPredictRequest
impl Message for BatchPredictRequest
source§fn encoded_len(&self) -> usize
fn encoded_len(&self) -> usize
source§fn encode(&self, buf: &mut impl BufMut) -> Result<(), EncodeError>where
Self: Sized,
fn encode(&self, buf: &mut impl BufMut) -> Result<(), EncodeError>where
Self: Sized,
source§fn encode_to_vec(&self) -> Vec<u8>where
Self: Sized,
fn encode_to_vec(&self) -> Vec<u8>where
Self: Sized,
source§fn encode_length_delimited(
&self,
buf: &mut impl BufMut,
) -> Result<(), EncodeError>where
Self: Sized,
fn encode_length_delimited(
&self,
buf: &mut impl BufMut,
) -> Result<(), EncodeError>where
Self: Sized,
source§fn encode_length_delimited_to_vec(&self) -> Vec<u8>where
Self: Sized,
fn encode_length_delimited_to_vec(&self) -> Vec<u8>where
Self: Sized,
source§fn decode(buf: impl Buf) -> Result<Self, DecodeError>where
Self: Default,
fn decode(buf: impl Buf) -> Result<Self, DecodeError>where
Self: Default,
source§fn decode_length_delimited(buf: impl Buf) -> Result<Self, DecodeError>where
Self: Default,
fn decode_length_delimited(buf: impl Buf) -> Result<Self, DecodeError>where
Self: Default,
source§fn merge(&mut self, buf: impl Buf) -> Result<(), DecodeError>where
Self: Sized,
fn merge(&mut self, buf: impl Buf) -> Result<(), DecodeError>where
Self: Sized,
self
. Read moresource§fn merge_length_delimited(&mut self, buf: impl Buf) -> Result<(), DecodeError>where
Self: Sized,
fn merge_length_delimited(&mut self, buf: impl Buf) -> Result<(), DecodeError>where
Self: Sized,
self
.source§impl PartialEq for BatchPredictRequest
impl PartialEq for BatchPredictRequest
source§fn eq(&self, other: &BatchPredictRequest) -> bool
fn eq(&self, other: &BatchPredictRequest) -> bool
self
and other
values to be equal, and is used
by ==
.impl StructuralPartialEq for BatchPredictRequest
Auto Trait Implementations§
impl Freeze for BatchPredictRequest
impl RefUnwindSafe for BatchPredictRequest
impl Send for BatchPredictRequest
impl Sync for BatchPredictRequest
impl Unpin for BatchPredictRequest
impl UnwindSafe for BatchPredictRequest
Blanket Implementations§
source§impl<T> BorrowMut<T> for Twhere
T: ?Sized,
impl<T> BorrowMut<T> for Twhere
T: ?Sized,
source§fn borrow_mut(&mut self) -> &mut T
fn borrow_mut(&mut self) -> &mut T
§impl<T> Instrument for T
impl<T> Instrument for T
§fn instrument(self, span: Span) -> Instrumented<Self>
fn instrument(self, span: Span) -> Instrumented<Self>
§fn in_current_span(self) -> Instrumented<Self>
fn in_current_span(self) -> Instrumented<Self>
source§impl<T> IntoRequest<T> for T
impl<T> IntoRequest<T> for T
source§fn into_request(self) -> Request<T>
fn into_request(self) -> Request<T>
T
in a tonic::Request